2 papers
cs.LG2026
Stress-Testing Neural Network Verifiers with Provably Robust Instances
David Troxell, Yulia Alexandr, Sofia Hunt +2
Neural network verifiers aim to provide formal guarantees on model behavior, but existing verification benchmarks are fundamentally limited by their lack of ground-truth labels. As…
cs.LG2026
Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
David Troxell, Noah Roemer, Guido Montúfar
Differentiable optimization layers are traditionally integrated in predict-then-optimize frameworks where a neural model estimates parameters that subsequently serve as fixed input…